A new algorithm for the downscaling of cloud fields

Kurzfassung

We present a novel algorithm for the downscaling of three-dimensional cloud fields. The goal of the algorithm is to add realistic subscale variability to a coarse field taking the resolved variability into account. The method is tested by coarse graining high-resolution sparse cumulus and broken stratocumulus clouds in the horizontal plane, downscaling these coarse fields back to the high resolution and comparing the radiative and microphysical properties of these downscaled fields with the original high-resolution fields. The resolutions of the cumulus and stratocumulus clouds used for this purpose are increased by a factor of four and ten, respectively. The downscaling decreases the errors in the flux transmittance and reflectance of the cumulus and stratocumulus cloud fields by at least a factor of ten and three, respectively, compared to utilising the coarse cloud fields. A novel aspect of our algorithm is the fact that it constrains the high-resolution fields of cloud liquid water content as well as the subscale cloud fraction. An alternative version that does not include cloud fraction information is less accurate, but still significantly better than using the coarse fields. The latter downscaling algorithm can also be utilised for the disaggregation of geophysical fields for which fractional coverages are not defined. Furthermore, the downscaling algorithm can be combined with our other algorithms to generate surrogate fields with other constraints, for example, surrogate clouds with a prescribed liquid water content height distribution.